Variability of Selected Soil Properties and Their Relationships with Soybean Yield

2003 ◽  
Vol 67 (4) ◽  
pp. 1296-1302 ◽  
Author(s):  
M. S. Cox ◽  
P. D. Gerard ◽  
M. C. Wardlaw ◽  
M. J. Abshire
Rhizosphere ◽  
2021 ◽  
pp. 100386
Author(s):  
Cláudia Regina Dias-Arieira ◽  
Fernando Júnior Ceccato ◽  
Erick Zobiole Marinelli ◽  
Jorge Luiz Boregio Vecchi ◽  
Giovani de Oliveira Arieira ◽  
...  

2016 ◽  
Vol 14 (3) ◽  
pp. e0207 ◽  
Author(s):  
Gustavo H. Dalposso ◽  
Miguel A. Uribe-Opazo ◽  
Jerry A. Johann

One of the problems that occur when working with regression models is regarding the sample size; once the statistical methods used in inferential analyzes are asymptotic if the sample is small the analysis may be compromised because the estimates will be biased. An alternative is to use the bootstrap methodology, which in its non-parametric version does not need to guess or know the probability distribution that generated the original sample. In this work we used a set of soybean yield data and physical and chemical soil properties formed with fewer samples to determine a multiple linear regression model. Bootstrap methods were used for variable selection, identification of influential points and for determination of confidence intervals of the model parameters. The results showed that the bootstrap methods enabled us to select the physical and chemical soil properties, which were significant in the construction of the soybean yield regression model, construct the confidence intervals of the parameters and identify the points that had great influence on the estimated parameters.


2012 ◽  
Vol 3 (4) ◽  
pp. 457-469
Author(s):  
N. I. A. Talha ◽  
I. E. Nasr EL-Din ◽  
B. A. Zamil ◽  
A. S. M. EL-Saady

2020 ◽  
Vol 36 (1-2) ◽  
pp. 367-375
Author(s):  
R. S. Oak ◽  
◽  
D. D. Sarode ◽  
J. B. Joshi ◽  
S. A. Chavan ◽  
...  

2012 ◽  
Vol 104 (5) ◽  
pp. 1443-1458 ◽  
Author(s):  
P. Anthony ◽  
G. Malzer ◽  
S. Sparrow ◽  
M. Zhang

2020 ◽  
Vol 118 ◽  
pp. 126070 ◽  
Author(s):  
Giovani Stefani Faé ◽  
Armen R. Kemanian ◽  
Gregory W. Roth ◽  
Charles White ◽  
John E. Watson

Weed Science ◽  
2003 ◽  
Vol 51 (6) ◽  
pp. 987-994 ◽  
Author(s):  
Krishna N. Reddy ◽  
Robert M. Zablotowicz ◽  
Martin A. Locke ◽  
Clifford H. Koger

A field study was conducted during 1997 to 2001 on a Dundee silt loam soil at Stoneville, MS, to examine the effects of rye and crimson clover residues on weeds, soil properties, soil microbial populations, and soybean yield in conventional tillage (CT) and no-tillage (NT) systems with preemergence (PRE)-only, postemergence (POST)-only, and PRE plus POST herbicide programs. Rye and crimson clover were planted in October, desiccated in April, and tilled (CT plots only) before planting soybean. Both cover-crop residues reduced density of barnyardgrass, broadleaf signalgrass, browntop millet, entireleaf morningglory, and hyssop spurge but did not affect yellow nutsedge at 7 wk after soybean planting (WAP) in the absence of herbicides. Densities of these weed species were generally lower with PRE-only, POST-only, and PRE plus POST applications than with no-herbicide treatment. Total weed dry biomass was lower when comparing CT (1,570 kg ha−1) with NT (1,970 kg ha−1), rye (1,520 kg ha−1) with crimson clover (2,050 kg ha−1), and PRE plus POST (640 kg ha−1) with PRE-only (1,870 kg ha−1) or POST-only (1,130 kg ha−1) treatments at 7 WAP. Soils with crimson clover had higher organic matter, NO3–N, SO4–S, and Mn, and lower pH compared with rye and no–cover crop soils. Total fungi and bacterial populations and fluorescein diacetate hydrolytic activity were higher in soil with crimson clover, followed by rye and no cover crop. Soybean yields were similar between CT (1,830 kg ha−1) and NT (1,960 kg ha−1), no cover crop (2,010 kg ha−1) and rye (1,900 kg ha−1), and rye and crimson clover (1,790 kg ha−1), but they were higher in PRE plus POST (2,260 kg ha−1) than in PRE-only (1,890 kg ha−1) or POST-only (1,970 kg ha−1) treatments.


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